New Solutions for Smart Buildings: From Research to Deployment

Speaker: Jessica Granderson, Staff Scientist, Lawrence Berkeley National Laboratory
Host: Energy Graduate Group
Date: 11/6/2020
Time: 10:30am to 11:50am
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Abstract: As the data revolution comes to buildings, we have seen a surge in new solutions for control and analytics. Researchers and smart buildings product developers are exploring how data science and machine learning, the internet of things, and cloud computing can transform building energy efficiency, operations, and maintenance. Correspondingly, there is an increasing need to understand how users are benefitting from new technologies, what the true costs are, and the most critical development opportunities to further to advance usability, scalability, and performance.

Dr. Granderson will present the state of the art in commercially available building energy analytics software, and results from the largest study ever conducted to document their as-installed costs, savings, and best practice uses. She will also share new research to integrate diagnostic and control capabilities, and to expand analytics through the use of novel data sources. This includes the application of engineering-based approaches and deep reinforcement learning to: embed active fault correction into fault diagnostics product offerings, and auto-generate 3D geometries and thermal profiles from aerial and drone-based images

Bio: Dr. Jessica Granderson is a Staff Scientist and the Deputy of Research Programs for the Building Technology and Urban Systems Division at the Lawrence Berkeley National Laboratory. She is a member of the Whole Building Systems Department. Dr. Granderson holds a PhD in Mechanical Engineering from UC Berkeley, and an AB in Mechanical Engineering from Harvard University. Her research focuses on building energy performance monitoring and diagnostics, advanced measurement and verification, and intelligent lighting controls. She is the recipient of the 2015 Clean Energy Education and Empowerment (C3E) Award for Leadership in Research and the 2020 Federal Laboratory Consortium Award for Excellence in Technology Transfer.